Data Science and Artificial Intelligence

Python Tutorial – Data Types in Python

In our previous post, we had looked into the Introduction of Python and its installation.
In all the programming languages programmers would work with data, so data types is one of the crucial ingredient of any programming language.
In Python, all the data types are represented in the form of objects; either built-in objects that Python provides, or objects that user creates using Python classes
Below are the core datatypes provided by Python.
Object type Example literals/creation
Numbers   1234, 3.1415, 3+4j, 0b111, Decimal(), Fraction()
Strings ‘Python’, “Programming”, b’a\x01c’, u’sp\xc4m’
Lists [1, [two, ‘eight’], 4.5], list(range(10))
Dictionaries {‘planet’: ‘star’, ‘asteroid’: ‘yum’}, dict(hours=10)
Tuples (1, ‘star’, 4, ‘U’), tuple(‘star’), namedtuple
In programming languages like Java, C++ , we  need to  explicitly declare the variable types. But In  python we  dont have to declare the variable types.
There is specific Python language syntax to create different objects.
Example:
When you run the below code,  i.e sequence of characters enclosed by single quotes, it will create String Object.
>>> ‘Python’
Similarly, an expression wrapped in square brackets makes a list, one in curly braces makes a dictionary, and so on. Even though there are no type declarations in Python, the syntax of the expressions you run determines the types of objects you create and use.
Now, let’s look at each datatype briefly.

Numbers:

In Python, all the numbers are represented in two types:

  1. Integers that have no fractional part,
  2. Floating-point numbers that contain fractional part and complex numbers with imaginary parts, decimals with fixed precision etc.

Numbers are immutable types in Python, i.e. changing the value of number data results in new Object.
Example:
Val1 = 27
python shelll
The above expression creates the variable named ‘val1’ and assigns integer value 27 to it.
Note: In Python, we dont have to specify the data type based on the syntax we used in the value python decides the type dynamically.
If we want to store floating point variable, then just assign decimal value to the variable.
 
python

Operations on Numbers:

We can perform all the basic mathematical operations on Python numbers Objects like addition, subtraction, multiplication, division etc.

Along with the expression, Python ships with some useful math packages. We just need to import them to use their functionality.

Math Module:

This module provide basic functions like pi, sqrt, ceil, floor etc.

 

Random Module:

If We want the computer to pick a random number in a given range, from a list, or pick a random card from a deck, flip a coin etc  for such applications we can use random module
Example:
Sample example for generating random integers between 1 to 8.  

Strings:

Strings are immutable collection of characters. In Python, strings can store textual characters or arbitrary collection of bytes (images file contents). In python string objects are stored in a sequence.
Sequences maintain a left-to-right order among the items  and are stored and fetched by their relative positions.
It’s very easy to create the strings objects in Python, any characters which are enclosed by quotes become string (quotes can ‘(single) or “(double)).
Example:
Creating sample string S1

Strings are objects in Python, using which we can perform some basic operations like finding the length of the string, to access character in some position etc.

 
Strings are immutable, meaning, we cannot change the values. If we try to change the value, we will get an error.

But if you want to change the string, we can run the expression and assign the changed object to the variable.

String Operations:

We  will be  performing following operations :

  • Converting a String from upper case to lowercase and vice versa

  • Finding the off set of the character in the string

  • Concatenation

Concatenating the string with ‘+’ operator, we can concatenate two strings.

  • Splitting the string with specific delimiter.

Lists:

Lists are collection of the same or different type of objects.
For example, a list can contain the details of customers, or students of the class, list of movie titles etc.
Now, we will create the list of customer names.

The above list is a collection of string objects. We can also create the list with different types of objects.

When you create a list in Python, the interpreter creates an array-like data structure in memory to hold your data, with your data items stacked from the bottom up. The first slot in the stack is numbered 0, the second is numbered 1, and the third is numbered 2, and so on.
To access items in the list, we should use the index position of that item starting from zero.

Operations on list:

Appending the element to the list.

deleting the element from list

Sorting the elements in List:

Reversing the order of elements in the list

Iterating over the collection

Dictionary:

The Python dictionary lets you organize your data by associating your data with names(keys) i.e. Mapping of values with keys.
Mappings don’t maintain any reliable left-to-right order; they simply map keys to associated values, and they can grow and shrink on demand.

Creating and Accessing Dictionary:


We can access the values by its associated key.

Operations on Dictionary:

Len function is used to find the number of elements in Dictionary.
We can do key membership test i.e. test whether the specified key is present in the Dictonary or not.

Converting keys of dictionary to list.

Adding and deleting the entries from Dictionary.

The Del method is used to remove item(s) from dictionary.

Getting values and keys from dictionary as a list.

Few Dictionary Examples:

Tuples:

The tuple object is roughly like a list that cannot be changed functionally. They’re used to represent fixed collections of items: the components of a specific calendar date, for instance.

Creating tuples and few basic operations on them.

Why use Tuples when we have lists?

Tuples are similar to lists, they support only few features than list.
only reason we use tuples because they are immutable, i.e.
Since collection of objects around your program passed  as a list, can be changed anywhere but if you use a tuple, it can’t be changed because of its immutability.
We hope this post id helpful in understanding the basics of Python datatypes. In our next post, we will discussing about Python statements.
In case of any queries, feel free to reach out to us at [email protected].
Keep visiting our site www.acadgild.com for more updates on Bigdata and other technologies.
 

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